1. Field of the Invention
The present invention relates to a method for measuring a voicing level used in a vocoder, and more particularly, to a method and an apparatus for determining multiband voicing levels using a frequency shifting method in a vocoder, which determines a voicing level based on autocorrelation.
2. Description of the Related Art
In general, a voice is represented by a pitch, a voicing level, and a vocal tract coefficient in a vocoder of low bit ratio. The pitch and the voicing level are modeled by an excite signal and the vocal tract coefficient is modeled by a transfer function. Here, the voicing level denotes a degree to which a voiced sound is included in a voice signal. The voicing level is one of the most important parameters for expressing a voice and plays a considerable role in determining the quality of the voice which passed through the vocoder. Therefore, a voicing level measuring method used for the vocoder has been constantly searched.
Traditionally, the voicing level simply determined the whole band to be voiced or unvoiced. This was employed in the LPC10:DoD 2.4 kbit/s standard vocoder. Dividing the voicing levels in two parts remarkably deteriorates the quality of the vocoder. Recently, a method in which the quality of sound is much improved is used. For example, in a multiband excitation (MBE) vocoder, the whole band is divided into a predetermined number of subbands in the frequency band of the voice and the respective subbands are determined to be voiced and unvoiced. Also, in a sinusoidal transform coder (STC), an analyze signal is expressed as a value between 0 and 1 by measuring periodical strengths of the analyze signal. According to the strengths, the band of the lowband frequency is determined to be voiced and the band of the highband frequency is determined to be unvoiced.
Methods of differently expressing the voiced levels in each subband are widely known.
First, there is the above-mentioned MBE vocoder method. In the MBE vocoder method, after normalizing the sum of the square of a difference between a synthesized spectrum obtained through modeling under the assumption that the whole band is voiced and an original spectrum, the normalized value is compared with previously set threshold values, thus determining whether the concerned band is voiced or unvoiced. Second, there is an STC method. While the MBE vocoder method determines the voicing levels on the spectrum, in the STC method, after normalizing the sum of the square between a synthesized periodical signal and an original signal in a time axis signal, the normalized value is compared with previously set thresholds, thus determining a voiced and unvoiced cut-off frequency. A spectral band less than the cut-off frequency and that more than the cut-off frequency are respectively determined to be voiced and unvoiced. In the above two methods, the voice levels are determined in each subband by comparing the difference between the original signal (or spectrum) and a synthesized signal (or spectrum) with the threshold value in a frequency or a time axis.
Third, there is an autocorrelation method of a time envelope signal. In this method, the voice signal is bandpass filtered for calculating a firm autocorrelation value in high frequency subband the time envelope of the filtered signal is estimated, and a normalized autocorrelation value is calculated from the estimated signal. The voicing levels of the respective spectral subbands are determined on the basis of the autocorrelation value. Fourth, there is an autocorrelation method of an upsampling signal. In this method, a time resolution is compensated by dividing the voice signal in each subband and performing upsampling with respect to the high frequency band. The normalized autocorrelation value is obtained from the upsampled signal and the voicing level is determined on the basis of the normalized autocorrelation value.
In the above two methods, the voicing levels are determined in each subband on the basis of the autocorrelation method. This is based on the fact that the autocorrelation value is larger as the voicing level of a voice is higher. Here, it is important how to calculate the autocorrelation value in the high frequency subband in which many errors are generated in calculating the autocorrelation value.